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首页> 外文期刊>Electric power systems research >EKF-based TS fuzzy prediction for eliminating the extremely fast reactive power variations in Manjil wind farm
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EKF-based TS fuzzy prediction for eliminating the extremely fast reactive power variations in Manjil wind farm

机译：基于EKF的TS模糊预测，消除了Manjil风电场极快的无功变化

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The inherent time-varying nature of the wind farm power causes undesired voltage flicker in the power network. In order to mitigate the flicker to enhance the performance of the wind power system with very fast dynamics, the static VAr compensator (SVC) is utilized. However, the SVC operates with some delays which negatively affects its performance. This persuades us to predict the reactive power of the wind farm to compensate for the real-world delay. The predicted reactive power is then utilized in the SVC. Therefore, this paper develops a novel fuzzy one-step-ahead prediction approach for the wind farm reactive power. The proposed fuzzy prediction uses a Takagi-Sugeno (TS) fuzzy representation whose unknown parameters are tuned online based on an extended Kalman filter (EKF). The wind farm is modeled as a time-varying current source which its amplitude and phase change every 0.01 s. A large set of the actual data of a wind farm in Manjil, Iran is gathered and directly utilized in the simulation process. Several flicker indices are calculated to evaluate the proposed prediction method. The obtained results show the performance enhancement and flicker mitigation of the suggested power scheme.
机译：风电场功率的固有时变性质导致电力网络中的不期望的电压闪烁。为了减轻闪烁以增强风电系统的性能，具有非常快速的动态，使用静态VAR补偿器（SVC）。但是，SVC运行了一些延迟，这对其性能产生负面影响。这使我们说服我们预测风电场的无功力量来弥补真实世界的延误。然后在SVC中使用预测的无功功率。因此，本文开发了一种用于风电场无功功率的新型模糊一步预测方法。所提出的模糊预测使用TAKAGI-SUGENO（TS）模糊表示，其未知参数基于扩展的卡尔曼滤波器（EKF）在线在线进行调整。风电场被建模为时变电流源，每0.01秒的幅度和相位变化。在Manjil的风电场的大量实际数据，伊朗收集并直接在模拟过程中使用。计算几种闪烁指数以评估所提出的预测方法。所获得的结果表明了建议的电力方案的性能增强和闪烁缓解。

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